Technical Field
The present invention relates generally to computer networking and data traffic management, and more particularly, to a virtualized data plane framework for centrally manage network resources across geographically distributed data centers.
Description of the Related Art
Growing demand for data and the increasing number of devices are drastically changing the scale of operation in Long-Term-Evolution (LTE) networks. With emergence of newer business models, services require more efficient provisioning with enhanced traffic management. Current LTE Core Network implementations are inflexible and inefficient to meet these requirements.
The rise of cloud computing has caused, and will continue to cause data traffic per smartphone to grow exponentially in the coming years (e.g., forecasted to 5 GB, with 25 billion connected devices by 2020). The coupled effect of the growth of devices and the data will require networks to operate at scale. Additionally, a saturated voice market and limited long-term growth from data access requires mobile operators to expand to newer business models, such as Internet of Things (IoT) based services, enterprise mobility, and vertical MVNOs. However, to enable such network-as-a-service business models, operators need additional capabilities for rapid provisioning of network resources of both the radio access and the core network. In the context of LTE core networks, current specialized hardware based deployments are not capable of efficiently and cost-effectively meeting these requirements.
Motivated by IT Clouds, (e.g., EC2) that can provide high reliability at lower costs, operators are considering Network Functional Virtualization (NFV) as a primary candidate for the first step towards evolving their networks. With virtualization, the network functions may be deployed over a platform based on commercially available hardware, enabling fast and agile provisioning. While operators do realize the benefits of NFV, its adoption in the core networks has been hindered due to the presence of several technical challenges. One of the primary challenge is the need to design a management layer that is tailored to the future requirements of LTE networks. Without efficient management, the network capacity may not be matched to the real-time traffic demands, leading to lower resource utilization and degraded traffic Quality of Service (QoS).